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eSMCs

Financiado

Cerrado

Extending Sensorimotor Contingencies to Cognition

The majority of current robot architectures is based on a perception-then-action control strategy. In this project, we will adopt a theoretical perspective that turns this classical view upside-down and emphasizes the constitutive... ver más

31/12/2014

UKE

5M€

Presupuesto del proyecto: 5M€

Líder del proyecto

UNIVERSITAETSKLINIKUM HAMBURGEPPENDORF No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Ver 7 Participantes

Financiación concedida El organismo FP7 notifico la concesión del proyecto el día 2014-12-31 No tenemos la información de la convocatoria

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Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

7 Participantes

UKE

0.00€ | Lider

UOS

N.D. | Participante

UPV

N.D. | Participante

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Líder del proyecto

UNIVERSITAETSKLINIKUM HAMBURGEPPENDORF No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 5M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto The majority of current robot architectures is based on a perception-then-action control strategy. In this project, we will adopt a theoretical perspective that turns this classical view upside-down and emphasizes the constitutive role of action for perception. The key concept our project is based on that of sensorimotor contingencies, that is, law-like relations between actions and associated changes in sensory input. We will advance this concept further and suggest that actions not only play a key role for perception, but also in developing more complex cognitive capabilities. We suggest that extended sensorimotor contingencies (eSMCs) may be exploited for the definition of object concepts and action plans and that their mastery can lead to goal-oriented behavior. The project pursues the following objectives: We will employ this approach to establish computational models that are suitable as controllers for autonomous robots; we will implement these eSMCs-based models on robotic platforms with different sensor-actuator equipment; we will investigate learning and adaptivity of eSMCs in artificial systems, focussing on sensorimotor interactions, object recognition and action planning; we will investigate and validate the concept of eSMCs in natural cognitive systems, by carrying out behavioural and neurophysiological studies on healthy human subjects; finally, we will test predictions derived from this concept in patients with movement dysfunctions, where ensueing changes in perceptual and cognitive processing will be tested. A set of benchmarks and task scenarios will be developed serving as demonstrators for the enhanced performance of artificial systems based on the eSMCs approach. Moreover, the usefulness of the approach for the development of applications in augmenting human behaviour will be demonstrated.

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